{"id":"https://openalex.org/W2092863353","doi":"https://doi.org/10.1109/icmla.2012.196","title":"ICMLA Face Recognition Challenge -- Results of the Team Computational Intelligence Mittweida","display_name":"ICMLA Face Recognition Challenge -- Results of the Team Computational Intelligence Mittweida","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2092863353","doi":"https://doi.org/10.1109/icmla.2012.196","mag":"2092863353"},"language":"en","primary_location":{"id":"doi:10.1109/icmla.2012.196","doi":"https://doi.org/10.1109/icmla.2012.196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2012.196","pdf_url":null,"source":{"id":"https://openalex.org/S4306419645","display_name":"International Conference on Machine Learning and Applications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 11th International Conference on Machine Learning and Applications","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027248793","display_name":"Thomas Villmann","orcid":"https://orcid.org/0000-0001-6725-0141","observed_orcids":["https://orcid.org/0000-0001-6725-0141"]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Villmann","raw_affiliation_strings":["University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]},{"raw_affiliation_string":"Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069055844","display_name":"Marika K\u00e4stner","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marika Kastner","raw_affiliation_strings":["University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]},{"raw_affiliation_string":"Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088903370","display_name":"David Nebel","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Nebel","raw_affiliation_strings":["University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]},{"raw_affiliation_string":"Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060927887","display_name":"Martin Riedel","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Riedel","raw_affiliation_strings":["University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences Mittweida, Computational Intelligence Group, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]},{"raw_affiliation_string":"Comput. Intell. Group, Univ. of Appl. Sci. Mittweida, Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116397343"],"apc_list":null,"apc_paid":null,"fwci":0.6653,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70983376,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"30","issue":null,"first_page":"592","last_page":"595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.04610000178217888,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/face-recognition","display_name":"face recognition","score":0.9959999918937683},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"learning vector quantization","score":0.7919999957084656},{"id":"https://openalex.org/keywords/data-preprocessing","display_name":"data preprocessing","score":0.675000011920929},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.9990000128746033},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.5659999847412109},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"computational intelligence","score":0.4880000054836273}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7308365106582642},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.6966572999954224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.674595832824707},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6531808972358704},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.608072817325592},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5932273268699646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5647474527359009},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.5619879961013794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5008766651153564},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4797700345516205},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.47200560569763184},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.404079794883728},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla.2012.196","doi":"https://doi.org/10.1109/icmla.2012.196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2012.196","pdf_url":null,"source":{"id":"https://openalex.org/S4306419645","display_name":"International Conference on Machine Learning and Applications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 11th International Conference on Machine Learning and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1510073064","https://openalex.org/W1563088657","https://openalex.org/W1585143937","https://openalex.org/W1588047250","https://openalex.org/W1679913846","https://openalex.org/W2039434802","https://openalex.org/W2083397249","https://openalex.org/W2094150678","https://openalex.org/W2098969718","https://openalex.org/W2103595817","https://openalex.org/W2123749980","https://openalex.org/W2124067153","https://openalex.org/W2202992072","https://openalex.org/W3151971511"],"related_works":["https://openalex.org/W205654272","https://openalex.org/W341112413","https://openalex.org/W1987893373","https://openalex.org/W7140262437","https://openalex.org/W106573348","https://openalex.org/W2403551073","https://openalex.org/W2322219984","https://openalex.org/W4255387718","https://openalex.org/W2394940487","https://openalex.org/W4414352052"],"abstract_inverted_index":{"The":[0],"contribution":[1],"describes":[2],"the":[3,6,12,20,30,47,52,65,75],"application":[4],"of":[5,14],"Team":[7],"'Computational":[8],"Intelligence":[9],"Group'":[10],"from":[11],"University":[13],"Applied":[15],"Sciences":[16],"Mittweida":[17],"(Germany)":[18],"to":[19],"ICMLA":[21],"Face":[22],"Recognition":[23],"Challenge":[24],"2012.":[25],"In":[26],"particular":[27],"we":[28,43],"explain":[29],"data":[31],"preprocessing":[32],"and":[33],"feature":[34],"extraction,":[35],"which":[36],"was":[37],"applied":[38],"before":[39],"classification":[40,49,71],"learning.":[41],"Further":[42],"give":[44],"details":[45],"about":[46,64],"used":[48],"algorithm":[50],"-":[51],"enhanced":[53],"generalized":[54],"matrix":[55],"learning":[56,76],"vector":[57],"quantization":[58],"model":[59],"(eGMLVQ).":[60],"We":[61],"provide":[62],"information":[63],"results":[66],"as":[67,69],"well":[68],"observed":[70],"properties":[72],"detected":[73],"by":[74],"algorithm.":[77]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":3}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
